{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:27:44Z","timestamp":1742912864838,"version":"3.40.3"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031199578"},{"type":"electronic","value":"9783031199585"}],"license":[{"start":{"date-parts":[[2022,10,21]],"date-time":"2022-10-21T00:00:00Z","timestamp":1666310400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,10,21]],"date-time":"2022-10-21T00:00:00Z","timestamp":1666310400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-19958-5_93","type":"book-chapter","created":{"date-parts":[[2022,10,20]],"date-time":"2022-10-20T11:06:59Z","timestamp":1666264019000},"page":"991-1004","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Hybrid Particle Swarm Optimization for a Feature Selection Problem with Stability Analysis"],"prefix":"10.1007","author":[{"given":"Debashis","family":"Dutta","sequence":"first","affiliation":[]},{"given":"Subhabrata","family":"Rath","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,10,21]]},"reference":[{"issue":"6","key":"93_CR1","doi-asserted-by":"publisher","first-page":"1656","DOI":"10.1109\/TSMCB.2012.2227469","volume":"43","author":"B Xue","year":"2013","unstructured":"Xue, B., Zhang, M., Browne, W.N.: Particle swarm optimization for Feature Selection in classification: a multi-objective approach. IEEE Trans. Cybern. 43(6), 1656\u20131671 (2013)","journal-title":"IEEE Trans. Cybern."},{"key":"93_CR2","unstructured":"Dheeru, D., Casey, G.: UCI machine learning repository (2017)"},{"key":"93_CR3","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","first-page":"333","DOI":"10.1007\/978-981-16-1740-9_28","volume-title":"Soft Computing: Theories and Applications","author":"D Dutta","year":"2022","unstructured":"Dutta, D., Rath, S.: Job scheduling on computational grids using multi-objective fuzzy particle swarm optimization. In: Sharma, T.K., Ahn, C.W., Verma, O.P., Panigrahi, B.K. (eds.) Soft Computing: Theories and Applications. AISC, vol. 1380, pp. 333\u2013347. Springer, Singapore (2022). https:\/\/doi.org\/10.1007\/978-981-16-1740-9_28"},{"key":"93_CR4","series-title":"Communications in Computer and Information Science","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1007\/978-981-16-4772-7_13","volume-title":"Computational Sciences \u2013 Modelling, Computing and Soft Computing","author":"D Dutta","year":"2021","unstructured":"Dutta, D., Rath, S.: Scheduling of jobs on computational grids by fuzzy particle swarm optimization algorithm using trapezoidal and pentagonal fuzzy numbers. In: Awasthi, A., John, S.J., Panda, S. (eds.) CSMCS 2020. CCIS, vol. 1345, pp. 175\u2013185. Springer, Singapore (2021). https:\/\/doi.org\/10.1007\/978-981-16-4772-7_13"},{"key":"93_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1007\/978-3-642-29139-5_9","volume-title":"genetic programming","author":"K Neshatian","year":"2012","unstructured":"Neshatian, K., Zhang, M.: Improving relevance measures using genetic programming. In: Moraglio, A., Silva, S., Krawiec, K., Machado, P., Cotta, C. (eds.) EuroGP 2012. LNCS, vol. 7244, pp. 97\u2013108. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-29139-5_9"},{"key":"93_CR6","doi-asserted-by":"crossref","unstructured":"Kennedy, J., Eberhart,. R.C.: A discrete binary version of the particle swarm algorithm. In: 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation, vol. 5, pp. 4104\u20134108. IEEE (1997)","DOI":"10.1109\/ICSMC.1997.637339"},{"key":"93_CR7","doi-asserted-by":"publisher","unstructured":"Proschan, F.M.: Wilcoxon-Mann-Whitney or t-test? On assumptions for hypothesistests and multiple interpretations of decision rules (2010). https:\/\/doi.org\/10.1214\/09-SS051","DOI":"10.1214\/09-SS051"},{"key":"93_CR8","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1016\/j.advengsoft.2017.07.002","volume":"114","author":"S Mirjalili","year":"2017","unstructured":"Mirjalili, S.: Salp swarm algorithm: a bio-inspired optimizer for engineering design problems. Adv. Eng. Softw. 114, 163\u2013191 (2017)","journal-title":"Adv. Eng. Softw."},{"key":"93_CR9","doi-asserted-by":"publisher","unstructured":"Gharehchopogh, H.F.M.S.: Feature selection. A novel hybrid whale optimization algorithm with flower pollination algorithm for feature selection: case study email spam detection. Comput. Intell. 176\u2013209 (2020). https:\/\/doi.org\/10.1111\/coin.12397","DOI":"10.1111\/coin.12397"},{"key":"93_CR10","doi-asserted-by":"crossref","unstructured":"Nguyen, H.B., Xue, B.,, Liu, I., Zhang, M.: Filter based backward elimination in wrapper based particle swarm optimization for Feature Selection in classification. In: IEEE Congress on Evolutionary Computation (CEC), pp. 3111\u20133118. IEEE (2014)","DOI":"10.1109\/CEC.2014.6900657"},{"key":"93_CR11","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1007\/978-3-030-68154-8_16","volume-title":"Intelligent Computing and Optimization. ICO 2020","author":"T Niyomsat","year":"2020","unstructured":"Niyomsat, T., Hlangnamthip, S., Puangdownreong, D.: Cooperative FPA-ATS algorithm for global optimization. In: Vasant, P., Zelinka, I., Weber, G.W. (eds.) ICO 2020. Advances in Intelligent Systems and Computing, vol. 1324, pp. 154\u2013163. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-68154-8_16"},{"issue":"4","key":"93_CR12","first-page":"899","volume":"5","author":"OH Babatunde","year":"2014","unstructured":"Babatunde, O.H., Armstrong, L., Leng, J., Diepeveen, D.: A Genetic algorithm-based feature selection. Int. J. Electron. Commun. Comput. Eng. 5(4), 899\u2013905 (2014)","journal-title":"Int. J. Electron. Commun. Comput. Eng."},{"issue":"8","key":"93_CR13","doi-asserted-by":"publisher","first-page":"1226","DOI":"10.1109\/TPAMI.2005.159","volume":"27","author":"H Peng","year":"2005","unstructured":"Peng, H., Long, F., Ding, C.: Feature Selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy. IEEE Trans. Pattern Anal. Mach. Intell. 27(8), 1226\u20131238 (2005)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"93_CR14","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","first-page":"190","DOI":"10.1007\/978-3-030-33585-4_19","volume-title":"Intelligent Computing and Optimization","author":"T Samakpong","year":"2020","unstructured":"Samakpong, T., Ongsakul, W., Nimal\u00a0Madhu, M.: Optimal power flow considering cost of wind and solar power uncertainty using particle swarm optimization. In: Vasant, P., Zelinka, I., Weber, G.-W. (eds.) ICO 2019. AISC, vol. 1072, pp. 190\u2013203. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-33585-4_19"},{"key":"93_CR15","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"605","DOI":"10.1007\/978-3-319-13563-2_51","volume-title":"simulated evolution and learning","author":"B Tran","year":"2014","unstructured":"Tran, B., Xue, B., Zhang, M., et al.: Overview of particle swarm optimisation for feature selection in classification. In: Dick, G. (ed.) SEAL 2014. LNCS, vol. 8886, pp. 605\u2013617. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-13563-2_51"},{"key":"93_CR16","doi-asserted-by":"publisher","first-page":"9400","DOI":"10.1109\/ACCESS.2016.2604738","volume":"4","author":"D Wu","year":"2016","unstructured":"Wu, D., Xu, S., Kong, F.: Convergence analysis and improvement of the chicken swarm optimization algorithm. IEEE Access 4, 9400\u20139412 (2016)","journal-title":"IEEE Access"},{"key":"93_CR17","doi-asserted-by":"publisher","first-page":"3741","DOI":"10.1007\/s00366-020-01028-5","volume":"37","author":"Y Zhang","year":"2021","unstructured":"Zhang, Y., Liu, R., Wang, X., Chen, H., Li, C.: Boosted binary Harris hawks optimizer and feature selection. Eng. Comput. 37, 3741\u20133770 (2021)","journal-title":"Eng. Comput."},{"key":"93_CR18","series-title":"Lecture Notes in Networks and Systems","doi-asserted-by":"publisher","first-page":"592","DOI":"10.1007\/978-3-030-93247-3_58","volume-title":"Intelligent Computing & Optimization","author":"M Y\u00fccel","year":"2022","unstructured":"Y\u00fccel, M., Bekda\u015f, G., Nigdeli, S.M.: Optimization of truss structures with sizing of bars by using hybrid algorithms. In: Vasant, P., Zelinka, I., Weber, G.-W. (eds.) ICO 2021. LNNS, vol. 371, pp. 592\u2013601. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-030-93247-3_58"}],"container-title":["Lecture Notes in Networks and Systems","Intelligent Computing & Optimization"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-19958-5_93","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,6]],"date-time":"2024-10-06T07:13:52Z","timestamp":1728198832000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-19958-5_93"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,21]]},"ISBN":["9783031199578","9783031199585"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-19958-5_93","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"type":"print","value":"2367-3370"},{"type":"electronic","value":"2367-3389"}],"subject":[],"published":{"date-parts":[[2022,10,21]]},"assertion":[{"value":"21 October 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICO","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing & Optimization","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hua Hin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Thailand","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 October 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 October 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ico2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.icico.info\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}